| 神经网络自适应控制算法的研究和MATLAB仿真 |
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| 引用本文： | 朱惠峰.神经网络自适应控制算法的研究和MATLAB仿真[J].船电技术,2006,26(3):39-42. |
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| 作者姓名： | 朱惠峰 |
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| 作者单位： | 武汉理工大学自动化学院,武汉,430070 |
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| 摘 要： | 本文针对神经网络系统跟踪输入信号时,由于误差总是存在导致学习过程难以结束的特点,以一种用BP 网络逼近对象的学习算法为基础,结合相应的控制算法加以改进,并得到了一种快速学习因子的选择方法。结合不同对象通过MATLAB进行仿真,均获得了满意的效果。仿真和分析表明,该算法能保证系统具有良好的动态品质。
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| 关 键 词： | BP网络 自适应控制算法 变学习因子 建模与仿真 |
| 文章编号： | 1003-4862（2006）03-0039-04 |
| 收稿时间： | 2006-02-22 |
| 修稿时间： | 2006年2月22日 |
Research and MATLAB Simulation on Neural Networks Adaptive Control Algorithm |
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| Zhu Huifeng.Research and MATLAB Simulation on Neural Networks Adaptive Control Algorithm[J].Marine Electric & Electronic Technology,2006,26(3):39-42. |
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| Authors: | Zhu Huifeng |
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| Institution: | School of Automation, Wuhan University of Technology, Wuhan 430070, China |
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| Abstract: | When neural network system follows an input signal, it is hard for the learning process to finish because there is always error. This paper improves a learning algorithm based on BP networks to approximate the plants combined with relative control algorithm, and a selection method for learning factors is obtained. Satisfactory results have been achieved by using MATLAB simulation on different plants. Simulation and analysis shows that the algorithm can guarantee that the system has good dynamic quality. |
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| Keywords: | BP network adaptive control algorithm variable learning factor modeling simulation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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